Triple
T12516354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lzip |
E299199
|
entity |
| Predicate | comparedWith |
P278
|
FINISHED |
| Object | gzip |
E299197
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: gzip | Statement: [lzip, comparedWith, gzip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: gzip Context triple: [lzip, comparedWith, gzip]
-
A.
gzip
chosen
gzip is a widely used GNU file compression utility that reduces file size using the DEFLATE algorithm, commonly producing .gz archives on Unix-like systems.
-
B.
Zip
"Zip" is a witty, patter-style show tune from the Rodgers and Hart musical *Pal Joey*, known for its satirical take on intellectual pretension.
-
C.
bzip2
bzip2 is a free and open-source data compression program known for its high compression ratios using the Burrows–Wheeler algorithm.
-
D.
Zip2
Zip2 was an early online city guide and business directory software company from the late 1990s that provided web-based publishing tools for newspapers.
-
E.
7zip
7zip is a high-compression open-source archive format commonly used for efficiently packaging and reducing the size of files.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541f80148190976d1d912fe155d0 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bbd58b88190baeb99380babf64f |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.